Title :
Applications of FORALL-formed computations in large scale stochastic dynamic programming
Author :
Hanson, F.B. ; Jarvis, D.J. ; Xu, H.H.
Author_Institution :
Lab. for Adv. Comput., Illinois Univ., Chicago, IL, USA
Abstract :
Data parallel broadcasting methods have been developed by taking the advantages of the properties of stochastic, nonlinear, continuous-time dynamical systems. The stochastic components include both Gaussian and Poisson random white noise. An example of a grand challenge level application is the resource management problem. The purpose of this paper is to demonstrate that broadcasting can be efficiently performed, if the computational functions are FORALL-formed, i.e. arrays are formed using FORALL-loops. Also, it is predicted that the parallel data vault mass storage method becomes efficient and flexible if the computational functions are FORALL-formed
Keywords :
dynamic programming; large-scale systems; parallel programming; random noise; resource allocation; stochastic programming; FORALL-formed computations; FORALL-loops; Gaussian noise; Poisson random white noise; data parallel broadcasting methods; large scale stochastic dynamic programming; parallel data vault mass storage method; resource management; stochastic nonlinear continuous time dynamical systems; Broadcasting; Computer applications; Cost function; Dynamic programming; Large-scale systems; Optimal control; Stochastic processes; Stochastic resonance; Stochastic systems; White noise;
Conference_Titel :
Scalable High Performance Computing Conference, 1992. SHPCC-92, Proceedings.
Conference_Location :
Williamsburg, VA
Print_ISBN :
0-8186-2775-1
DOI :
10.1109/SHPCC.1992.232650